Adaptive indexing is a promising alternative to classical offline index optimization. Under adaptive indexing, index creation and re-organization take place automatically and incrementally as a side-effect of query execution. Over time, the index's structure converges to an idealized form suitable for the workload it is being used for. However, the ideal representation changes over time: An adaptive index that is initially optimal for one workload becomes suboptimal as the workload's characteristics change. Recent work has hinted at the possibility of a radical new class of adaptive indexes called just-in-time data structures that adapt their layout to rapidly changing workloads. A just-in-time data structure (JITD) can emulate the structure and performance characteristics of a variety of static and adaptive indexing schemes, while being able to gracefully transition between them in response to changing workloads. If successful, the proposed research will realize this radical new class of index structures by (1) generalizing preliminary work in this area to emulate a broader class of index structures and performance tradeoffs, (2) identifying opportunities for automation in the design of a JITD, (3) addressing practical challenges such as concurrency in JITDs, and (4) further generalizing JITDs to a new class of workload: incremental view maintenance. -- Intellectual Merit -- JITDs represent a new direction in research on indexing and physical layout design for data management systems that combines elements of programming language design with more classical database techniques. The proposed work will demonstrate the generality of the JITD model, and establish groundwork for future research in the area through specification languages, a compiler, and a generalization of functional datastructures and lazy evaluation that promises to have significant consequences for work on distributed computation. -- Broader Impact -- Index and physical layout design are a critical part of making data management systems perform well. If successful, the proposed work promises to enable a new class of index structures that dynamically adapt to changing workloads. This in turn promises to help next generation data management systems cope with the variability, volume, and velocity of big data. This proposal will also result in the education and training of two PhD students, and help to support the core curriculum development and outreach goals of the PIs. The PIs have a long history of outreach at the K-12 level, and routinely work with and provide professional development opportunities for local high-school teachers. -- Keywords -- Data Structures; Indexing; View Maintenance; Compilers; Physical Design; Programming Languages